Dataset Information

Hospital quality: a PRIDIT approach.

ABSTRACT:

Background

Access to high quality medical care is an important determinant of health outcomes, but the quality of care is difficult to determine.

Objective

To apply the PRIDIT methodology to determine an aggregate relative measure of hospital quality using individual process measures.

Design

Retrospective analysis of Medicare hospital data using the PRIDIT methodology.

Subjects

Four-thousand-two-hundred-seventeen acute care and critical access hospitals that report data to CMS' Hospital Compare database.

Measures

Twenty quality measures reported in four categories: heart attack care, heart failure care, pneumonia care, and surgical infection prevention and five structural measures of hospital type.

Results

Relative hospital quality is tightly distributed, with outliers of both very high and very low quality. The best indicators of hospital quality are patients given assessment of left ventricular function for heart failure and patients given beta-blocker at arrival and patients given beta-blocker at discharge for heart attack. Additionally, teaching status is an important indicator of higher quality of care.

Conclusions

PRIDIT allows us to rank hospitals with respect to quality of care using process measures and demographic attributes of the hospitals. This method is an alternative to the use of clinical outcome measures in measuring hospital quality. Hospital quality measures should take into account the differential value of different quality indicators, including hospital "demographic" variables.

SUBMITTER: Lieberthal RD

PROVIDER: S-EPMC2442235 | biostudies-literature | 2008 Jun

REPOSITORIES: biostudies-literature

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Publications

Hospital quality: a PRIDIT approach.

Lieberthal Robert D RD

Health services research 20080601 3

<h4>Background</h4>Access to high quality medical care is an important determinant of health outcomes, but the quality of care is difficult to determine.<h4>Objective</h4>To apply the PRIDIT methodology to determine an aggregate relative measure of hospital quality using individual process measures.<h4>Design</h4>Retrospective analysis of Medicare hospital data using the PRIDIT methodology.<h4>Subjects</h4>Four-thousand-two-hundred-seventeen acute care and critical access hospitals that report d ...[more]

PMID: 18454777

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Project description:Although regulatory improvements for air quality in the European Union have been made, air pollution is still a pressing problem and, its impact on health, both mortality and morbidity, is a topic of intense research nowadays. The main goal of this work is to assess the impact of the exposure to air pollutants on the number of daily hospital admissions due to respiratory causes in 58 spatial locations of Portugal mainland, during the period 2005-2017. To this end, INteger Generalised AutoRegressive Conditional Heteroskedastic (INGARCH)-based models are extensively used. This family of models has proven to be very useful in the analysis of serially dependent count data. Such models include information on the past history of the time series, as well as the effect of external covariates. In particular, daily hospitalisation counts, air quality and temperature data are endowed within INGARCH models of optimal orders, where the automatic inclusion of the most significant covariates is carried out through a new block-forward procedure. The INGARCH approach is adequate to model the outcome variable (respiratory hospital admissions) and the covariates, which advocates for the use of count time series approaches in this setting. Results show that the past history of the count process carries very relevant information and that temperature is the most determinant covariate, among the analysed, for daily hospital respiratory admissions. It is important to stress that, despite the small variability explained by air quality, all models include on average, approximately two air pollutants covariates besides temperature. Further analysis shows that the one-step-ahead forecasts distributions are well separated into two clusters: one cluster includes locations exclusively in the Lisbon area (exhibiting higher number of one-step-ahead hospital admissions forecasts), while the other contains the remaining locations. This results highlights that special attention must be given to air quality in Lisbon metropolitan area in order to decrease the number of hospital admissions.

Project description:BACKGROUND:Starting in fiscal year 2013, the Hospital Value-Based Purchasing (HVBP) program introduced quality performance-based adjustments of up to 1% to Medicare reimbursements for acute care hospitals. METHODS:We evaluated whether quality improved more in acute care hospitals that were exposed to HVBP than in control hospitals (Critical Access Hospitals, which were not exposed to HVBP). The measures of quality were composite measures of clinical process and patient experience (measured in units of standard deviations, with a value of 1 indicating performance that was 1 standard deviation [SD] above the hospital mean) and 30-day risk-standardized mortality among patients who were admitted to the hospital for acute myocardial infarction, heart failure, or pneumonia. The changes in quality measures after the introduction of HVBP were assessed for matched samples of acute care hospitals (the number of hospitals included in the analyses ranged from 1364 for mortality among patients admitted for acute myocardial infarction to 2615 for mortality among patients admitted for pneumonia) and control hospitals (number of hospitals ranged from 31 to 617). Matching was based on preintervention performance with regard to the quality measures. We evaluated performance over the first 4 years of HVBP. RESULTS:Improvements in clinical-process and patient-experience measures were not significantly greater among hospitals exposed to HVBP than among control hospitals, with difference-in-differences estimates of 0.079 SD (95% confidence interval [CI], -0.140 to 0.299) for clinical process and -0.092 SD (95% CI, -0.307 to 0.122) for patient experience. HVBP was not associated with significant reductions in mortality among patients who were admitted for acute myocardial infarction (difference-in-differences estimate, -0.282 percentage points [95% CI, -1.715 to 1.152]) or heart failure (-0.212 percentage points [95% CI, -0.532 to 0.108]), but it was associated with a significant reduction in mortality among patients who were admitted for pneumonia (-0.431 percentage points [95% CI, -0.714 to -0.148]). CONCLUSIONS:In our study, HVBP was not associated with improvements in measures of clinical process or patient experience and was not associated with significant reductions in two of three mortality measures. (Funded by the National Institute on Aging.).

Dataset Information

Hospital quality: a PRIDIT approach.

Background

Objective

Design

Subjects

Measures

Results

Conclusions

Publications

Hospital quality: a PRIDIT approach.

Similar Datasets

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